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Language Skills

R
MATLAB
Python
Bash

Open Source Contributions

All projects available at github.com/mathesong/<name>

More info

See full CV for more complete list of positions and publications.

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Last updated on 2020-04-09.

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Granville Matheson

I am an academic data scientist with a background in neuroscience. I am a generalist, but my speciality is in statistical modelling and inference, as well as presentation and communication. My work has made international news and been cited in policy1, I have been involved in developing field-wide guidelines to improve replicability2 and several R packages that I developed are used internationally. I am passionate about learning new things, and enjoy the challenge of presenting complex results in a compelling way to audiences with different backgrounds.

I am currently looking for a position that allows me to work with complex data to derive useful insights, and to develop tools to streamline the process and make it reproducible.

Education

PhD, Neuroscience

Stockholm, Sweden

Karolinska Institutet

2018 - 2014

  • Thesis: Reliability, Replicability and Reproducibility in PET Imaging
  • Working with PET imaging of the dopamine system in psychosis and proneness to developing psychosis, as well as methods development.

MSc, Neuroscience

Utrecht, The Netherlands

Universiteit Utrecht

2013 - 2010

Selected Positions

Postdoctoral Researcher*

Columbia University

Molecular Imaging / Biostatistics

2022 - 2020

  • * Cancelled / indefinitely postponed on account of COVID-19 pandemic (NYC)
  • Developing Bayesian methods for performing pharmacokinetic modelling using a multilevel framework, with Markov Chain Monte Carlo.

Research Assistant

Karolinska Institutet

Cervenka Lab, PET Group

2014 - 2012

  • Image processing and analysis of MR and PET Imaging data to produce the Karolinska Behavioural PET Database

Selected Writing

Nonlinear Modelling using nls, nlme and brms

granvillematheson.com

N/A

2020

  • A demonstration of how to fit nonlinear models using standard gradient descent optimisation, as well as both frequentist and Bayesian multilevel modelling strategies

My Physiological Response to my PhD Defence3

granvillematheson.com

N/A

2018

  • I recorded my physiological data in the months leading up to my PhD defence, and analysed it here, using data visualisation to tell the story of my sleep changes, and heart rate, both before and during the defence.
  • I also wrote an R package for extracting this data from the Withings API. This software is now used internationally.